In an image including pixels each formed by a plurality of components, a correlation (a correlative relation) among the components is high (strong) in some cases. When an image including pixels having a high correlation among the components is to be compressed, it may be possible to perform efficient compression by using one component for approximation of other components.
Inter-color-component prediction is known as image compression (coding) based on the correlation among components. In this image compression, the components are classified into a reference component and non-reference components. The reference component is coded (compressed) with a variable length code. The non-reference components are each predicted with a primary equation (a linear equation) using the reference component, so that a slope and an intercept (a prediction coefficient) of the linear equation are coded. In this image compression, reduction in the code amount required for compression of the non-reference components is achieved by compressing the slopes and the intercepts of the linear equations instead of compressing the non-reference components themselves.
However, compression of the slopes and the intercepts of the linear equations requires a large code amount for some correlations among the components.